Multidimensional data visualization methods are a modern tool allowing to classify some analysed objects. In the case of grained materials e.g. coal, many characteristics have an influence on the material quality. The paper presents the possibility of applying visualization techniques for coal type identification and determination of significant differences between various types of coal. To achieve this purpose, the method of Kohonen maps was applied by means of which three types of coal -31, 34.2 and 35 (according to Polish classification of coal types) were investigated. It was stated that the applied methodology allows to identify certain coal types efficiently and can be used as a qualitative criterion for grained materials.Keywords: Kohonen maps, grained material analysis, coal, multidimensional data, multidimensional visualization methods Metody wizualizacji wielowymiarowych danych są nowoczesnym narzędziem umożliwającym klasyfikację analizowanych obiektów, którymi mogą być różnego typu dane opisujące wybrane zjawisko lub materiał. W przypadku materiałów uziarnionych, jakim jest np. węgiel, wiele cech ma wpływ na jakość materiału, tj. np. gęstość, wielkość ziaren, ciepło spalania, zawartość popiołu, zawartość siarki itp. Na potrzeby artykułu przeprowadzono rozdział węgli z trzech wybranych kopalni węgla kamiennego, zlokalizowanych w Górnośląskim Okręgu Przemysłowym. Każda z tych kopalni pracuje na innego typu węglu. W tym przypadku były to węgle o typach 31, 34.2 oraz 35 (według polskiej klasyfikacji typów węgla). Najpierw, materiał został podzielony na klasy ziarnowe a następnie za pomocą rozdziale w cieczy ciężkiej (roztwór chlorku cynku) na frakcje gęstościowe. Dla tak przygotowanego materiału przeprowadzono następnie analizy chemiczne mające na celu określenie takich parametrów, jak zawartość siarki, zawartość popiołu, zawartość części lotnych, ciepło spalania oraz wilgotność analityczną. W ten sposób, dla każdej klaso-frakcji uzyskano bogate charakterystyki badanego materiału. Nasuwa się więc pytanie, czy możliwa jest identyfikacja typu węgla za pomocą dostępnych danych. W tym celu zastosowano
Abstract. The coal gasification process is one of the technologies which gain more and more attention among technologists dealing with processing and utilization of coal. In case of ground gasification, one of such technologies is fluidized bed gasification. For such gasification the guidelines were elaborated within the scientific project of NCBiR no. 23.23.100.8498/R34 Authors chose main of these guidelines, concerning the required levels of certain coal features. In purpose of investigating coal for its suitability to gasification, samples were collected from two Polish mines: ZG Janina and ZG Wieczorek and processed properly. The methods being used to visualization of multidimensional data through transformation of multidimensional space into two-dimensional space allow to present multidimensional data on computer screen. Among such methods, relevance maps method can be found which was used in this paper to present and analyze set of seven-dimensional data describing coal samples originating from both mines. It was decided to check whether this method of visualization of multidimensional data allows to divide the samples space into subspaces of various usefulness to the process of fluidal gasification or not. The method enables the visualisation of the optimal subspace containing the set requirements concerning the properties of coals intended for this process.
The dominant challenge of current copper beneficiation plants is the low recoverability of oxide copper-bearing minerals associated with sulfide type ones. Furthermore, applying commonly used conventional methodologies does not allow the interactional effects of critical parameters in the flotation processes to be investigated, which is mostly overlooked in the literature. To tackle this issue, the present paper aimed at characterizing the behavior of five key effective factors and their interactions in a sulfidized copper ore. In this context, dosage of collector (sodium di-ethydithiophosphate, 60–100 g/t), depressant (sodium silicate, 80–120 g/t) and frother (methyl isobutyl carbinol (MIBC), 6–10 g/t), pulp pH (7–11) and agitation rate (900–1300 rpm) were examined and statistically analyzed using response surface methodology. Flotation experiments were conducted in a Denver type agitated flotation cell at the rougher stage. The experimental results showed that increasing the pH (from 8 to 10) at low agitation rate (1000 rpm) enhanced the recovery from 80.36% to 85.22%, while at high agitation rate (1200 rpm), a slight declination occurred in the recovery. Meanwhile, increasing the collector dosage at a lower frother value (7 g/t), caused a reduction of about 4.44% in copper recovery owing to the interactions between factors, whereas at a higher frother level (9 g/t), the recovery was almost unchanged. The optimization process was also performed using the goal function approach, and maximum copper recovery of 92.75% was obtained using ~70 g/t collector, 110 g/t depressant, 7 g/t frother, pulp pH of 10 and 1000 rpm agitation rate.
The application of methods drawing upon multi-parameter visualization of data by transformation of multidimensional space into two-dimensional one allow to show multi-parameter data on computer screen. Thanks to that, it is possible to conduct a qualitative analysis of this data in the most natural way for human being, i.e. by the sense of sight. An example of such method of multi-parameter visualization is multidimensional scaling. This method was used in this paper to present and analyze a set of seven-dimensional data obtained from Janina Mining Plant and Wieczorek Coal Mine. It was decided to examine whether the method of multi-parameter data visualization allows to divide the samples space into areas of various applicability to fluidal gasification process. The "Technological applicability card for coals" was used for this purpose [Sobolewski et al., 2012;2013], in which the key parameters, important and additional ones affecting the gasification process were described.Keywords: coal gasification, multidimensional visualization, multidimensional scaling, MDS, multidimensional data, jiggingMetody służące do wizualizacji złożonych, wielowymiarowych danych poprzez transformację przestrzeni wielowymiarowej do dwuwymiarowej umożliwiają prezentację tych danych na ekranie komputera. Tym samym są przystępnym instrumentem analizy zbiorów danych, pozwalającym wykorzystać połączenie naszego wzroku z mocą naszej osobistej sieci neuronowej (mózgu) do wyodrębnienia z danych cech, których zauważenie przy pomocy innych metod może być bardzo trudne. W artykule zastosowano jedną z takich metod -skalowanie wielowymiarowe -w celu sprawdzenia, skuteczności tej metody do analizy próbek węgla ze względu na jego przydatność do procesu zgazowania w kotle fluidalnym. W tym celu pobrano próbki dwóch węgli, z KWK "Wieczorek" (węgiel typu 32) oraz ZG "Janina" (węgiel typu 31.2), które następnie miały być poddane testom pod względem ich przydatności do zgazowania. Każda z próbek została zbadana ze względu na cechy, których określone poziomy są kluczowe oraz wskazane w kontekście procesu zgazowania według "Karty przydatności węgli do zgazowania" (Sobolewski et al., 2012;2013).Każdy z węgli został rozdzielony na osadzarce pierścieniowej (10 pierścieni, uziarnienie węgla 0-18 mm) w wyniku czego powstało pięć warstw (po 2 pierścienie każda). Następnie każda z warstw została rozsiana na 10 klas ziarnowych. Tak otrzymane produkty zostały poddane technicznej oraz chemicznej analizie (ogółem 50 próbek z ZG "Janina" oraz 49 próbek z KWK "Wieczorek" -klasa ziarnowa 16-18 mm w tej drugiej kopalni nie została uzyskana i pomiar był niemożliwy do zrealizowania. Tym samym otrzymano takie parametry do analizy jak: zawartość siarki, zawartość wodoru, zawartość azotu, zawartość chloru, zawartość węgla organicznego, ciepło spalania oraz zawartość popiołu. W wyniku przeprowadzonych badań oraz porównania ich z wymogami prezentowanymi w "Karcie przydatności węgli do zgazowania" okazało się, że tylko 18 próbek spełnia wszystkie wymogi, z czego aż 17 pochodzi...
Coal as energetic raw material features by many parameters determining its quality. In classification of coal types there are many of them with typical division of energetic, semi-coking and coking coal. The data concerning coal are usually treated as independent values while this kind of approach is not always right. Authors proposed new solutions in this aspect and performed the multidimensional analysis of three selected types of coal featuring by various properties which originated from three various hard coal mines located in Upper Silesia Region. The object of the research was so-called raw coal which was not processed before. For each type of coal the detailed statistical analysis of seven chosen properties of coal was performed. To perform adequate and complete statistical analysis it is necessary to analyze the chosen properties of coal together in multidimensional way. It was decided to apply new and modern visualizing methods of multidimensional data which were observational tunnels method and parallel coordinates method. The applied methods allowed to obtain visualization of seven-dimensional data describing coal. By means of these visualizations it was possible to observe the significant division of the features space between researched types of coal. These methods allowed to look at the investigated data from various perspectives and make possible to determine significant differences between researched materials. For the investigated coals such differences were determined clearly what proved that by means of these methods it is possible to successfully identify type of coal as well to analyze in details its individual properties and identify, for example, particle size fraction etc. The obtained results are innovative and are the basis for more detailed researches taking into consideration also other coal properties, including its structure and texture. This methodology can be also applied successfully for other types of raw materials, like ores.
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